AstraZeneca

Generative AI Cloud Operations Engineer - Evinova

AstraZeneca$134K — $202K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • HS Diploma or GED required
  • Minimum of 2 years in deploying and maintaining Generative AI agents
  • Deep experience with challenges in Generative AI deployment
  • Familiarity with the Data Science Lifecycle (DSLC)
  • Expert in eval tools for LLMs, e.g., Arize Phoenix, Langfuse
  • Strong skills in Python/TypeScript and CDK
  • Proven ability to collaborate across various technical teams

Responsibilities

  • Drive proactive capability and process enhancements for value creation
  • Design resilient cloud operations for Generative AI agents
  • Develop systems for clinical trial optimization
  • Integrate and optimize LLM proxies and routers
  • Collaborate to transition projects from research to production
  • Leverage and teach modern tools for AI deployment
  • Enhance scalability and reliability of AI systems

Benefits

  • 401(k) plan for retirement contributions
  • Paid vacation and holidays
  • Health benefits including medical and dental coverage
  • Short-term and long-term incentive bonus opportunities
  • Paid leaves available
Full Job Description
Job Title: Generative AI Cloud Operations Engineer - Evinova
Location: Gaithersburg, MD

Introduction to Role:

The Machine Learning and Artificial Intelligence Operations team (ML/AI Ops) is a newly formed platform team that will spearhead the design, creation, and operational excellence of our LLM-based agent deployments, multi-agent orchestration, and conversational AI systems pipelines to catalyze and accelerate science led innovations.

This team is responsible and accountable for the design, implementation, deployment, health and performance of all LLM-based applications. We manage ML/AI and broader cloud resources, automating operations through infrastructure-as-code and CI/CD pipelines, and ensure best-in-class operations - striving to push even beyond mere compliance with industry standards such as Good Clinical Practices (GCP) and Good Machine Learning Practice (GMLP).

As a Generative AI Cloud Operations Engineer for clinical trial design, planning, and operational optimization on our team, you will lead the development and management of AI operations systems for our trial management and optimization SaaS product. You will collaborate closely with our AI Engineers to transition projects from embryonic research into production-grade AI capabilities, utilizing advanced tools and frameworks to optimize model deployment, governance, and infrastructure performance.

This position requires a deep understanding of cloud-native agentic Generative AI deployment methodologies and technologies, AWS infrastructure, and the unique demands of regulated industries, making it a cornerstone of our success in delivering impactful solutions to the pharmaceutical industry.

Accountabilities:

Operational Excellence
  • Drive the creation of proactive capability and process enhancements that ensures enduring value creation and analytic compounding interest.
  • Design and implement resilient cloud Genereative AI agent operational capabilities to maximize our system A-bilities (Learnability, Flexibility, Extendibility, Interoperability, Scalability).
  • Drive precision and systemic cost efficiency, optimized system performance, and risk mitigation with a data-driven strategy, comprehensive analytics, and predictive capabilities at the tree-and-forest level of our Generative AI-based systems, workloads and processes.

ML/AI Cloud Operations and Engineering
  • Develop and manage GenAI Ops systems for clinical trial design, planning and operational optimization.
  • Integrate LLM proxies/routers including LiteLLM Proxy/Router or other solutions
  • Ensure proper RAG pipeline optimization and scaling
  • Integration of token usage, latency, response quality, and hallucination detection tools at a platform level.
  • Partner closely with AI Engineers and data scientists to shepherd projects from embryonic research stages into production-grade agentic Generative AI capabilities.
  • Leverage and teach modern tools, libraries, frameworks and best practices to design, validate, deploy and monitor Generative AI agents in production (including LangChain, LangGraph, Google ADK, Langfuse, DSPy, Arize Phoenix, Pinecone, Weaviate, Splunk, Grafana, Prometheus, Xray, and more)
  • Enhance system scalability, reliability, and performance through effective infrastructure and process management.
  • Ensure that any prediction we make is backed by deep exploratory data analysis and evidence, interpretable, explainable, safe, and actionable.
  • Leverage Vertex AI, Azure Foundry, OpenAI, Anthropic, and other foundation model platforms to provide reliable and stable access to LLMs

Personal Attributes:
  • Customer-obsessed and passionate about building products that solve real-world problems.
  • Highly organized and detail-oriented, with the ability to manage multiple initiatives and deadlines.
  • Collaborative and inclusive, fostering a positive team culture where creativity and innovation thrive.
  • Know when to ask for help and when to help others proactively.


Essential Skills/Experience:
  • HS Diploma or GED
  • Minimum of 2 years deploying and maintaining Generative AI agents or GenAI-based workflows/applications in production.
  • Deep understanding of challenges in deploying Generative AI applications and agents.
  • Closely follows frontier developments in Generative AI and GenAI tooling, techniques, and technologies.
  • Deep understanding of the Data Science Lifecycle (DSLC) and the ability to shepherd data science projects from inception to production within the platform architecture.
  • Expert in evals tools for LLMs using tools such as Arize Phoenix, Langfuse, Braintrust, Freeplay, or similar.
  • Expert in CDK for python and/or TypeScript
  • Strong software engineering abilities in Python/TypeScript
  • Expert in AWS services and containerization technologies like Docker and Kubernetes.
  • Experience deploying GenAI agents using frameworks such as LangChain, LangGraph, LlamaIndex, Google ADK, or Strands Agents.
  • Ability to collaborate effectively with engineering, design, product, and science teams.
  • Strong written and verbal communication skills for reporting and documentation.
  • Proven track record of deploying algorithms and machine learning models into production environments.
  • Demonstrated ability to work closely with cross-functional teams, particularly data scientists.


Where can I find out more?
  • Learn more about Evinova www.evinova.com
  • Our Social Media, Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/
  • Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/
  • Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en
  • Our US Footprint: Powering Scientific Innovation - YouTube


Total Rewards:

The annual base pay for this position ranges from $134,866.40 to $202,299.60 Hourly and salaried non-exempt employees will also be paid overtime pay when working qualifying overtime hours. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program (salaried roles), to receive a retirement contribution (hourly roles), and commission payment eligibility (sales roles). Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an "at-will position" and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

#LI-Hybrid

Date Posted
26-Feb-2026

Closing Date

About AstraZeneca

AstraZeneca is a British-Swedish multinational pharmaceutical company that specializes in the research, development, and manufacturing of prescription drugs. The company was formed in 1999 through the merger of Astra AB and Zeneca Group plc. AstraZeneca's products are used to treat a wide range of medical conditions, including cancer, cardiovascular disease, respiratory disease, and diabetes. The company has operations in over 100 countries and employs more than 76,000 people worldwide. AstraZeneca is committed to developing innovative medicines that improve the health and well-being of people around the world.
Learn more about AstraZeneca
Size
83,100 employees
Market Cap
$211.5 billion
Industry
Net Income
$3.1 billion
Founded
1999
5 Year Trend
+10.2%
Revenue
$26.6 billion
NASDAQ

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